Diagnosis of boreal summer intraseasonal oscillation in high resolution NCEP climate forecast system

2015 ◽  
Vol 46 (9-10) ◽  
pp. 3287-3303 ◽  
Author(s):  
S. Abhik ◽  
P. Mukhopadhyay ◽  
R. P. M. Krishna ◽  
Kiran D. Salunke ◽  
Ashish R. Dhakate ◽  
...  
2009 ◽  
Vol 22 (24) ◽  
pp. 6561-6576 ◽  
Author(s):  
Wanqiu Wang ◽  
Mingyue Chen ◽  
Arun Kumar

Abstract Impacts of the ocean surface on the representation of the northward-propagating boreal summer intraseasonal oscillation (NPBSISO) over the Indian monsoon region are analyzed using the National Centers for Environmental Prediction (NCEP) coupled atmosphere–ocean Climate Forecast System (CFS) and its atmospheric component, the NCEP Global Forecast System (GFS). Analyses are based on forecasts of five strong NPBSISO events during June–September 2005–07. The inclusion of an interactive ocean in the model is found to be necessary to maintain the observed NPBSISO. The atmosphere-only GFS is capable of maintaining the convection that propagates from the equator to 12°N with reasonable amplitude within the first 15 days, after which the anomalies become very weak, suggesting that the atmospheric internal dynamics alone are not sufficient to sustain the anomalies to propagate to higher latitudes. Forecasts of the NPBSISO in the CFS are more realistic, with the amplitude of precipitation and 850-mb zonal wind anomalies comparable to that in observations for the entire 30-day target period, but with slower northward propagation compared to that observed. Further, the phase relationship between precipitation, sea surface temperature (SST), and surface latent heat fluxes associated with the NPBSISO in the CFS is similar to that in the observations, with positive precipitation anomalies following warm SST anomalies, which are further led by positive anomalies of the surface latent heat and solar radiation fluxes into the ocean. Additional experiments with the atmosphere-only GFS are performed to examine the impacts of uncertainties in SSTs. It is found that intraseasonal SST anomalies 2–3 times as large as that of the observational bulk SST analysis of Reynolds et al. are needed for the GFS to produce realistic northward propagation of the NPBSISO with reasonable amplitude and to capture the observed phase lag between SST and precipitation. The analysis of the forecasts and the experiments suggests that a realistic representation of the observed propagation of the oscillation by the NCEP model requires not only an interactive ocean but also an intraseasonal SST variability stronger than that of the bulk SST analysis.


2017 ◽  
Vol 74 (10) ◽  
pp. 3339-3366 ◽  
Author(s):  
B. B. Goswami ◽  
B. Khouider ◽  
R. Phani ◽  
P. Mukhopadhyay ◽  
A. J. Majda

Abstract A stochastic multicloud model (SMCM) convective parameterization, which mimics the interactions at subgrid scales of multiple cloud types, is incorporated into the National Centers for Environmental Prediction (NCEP) Climate Forecast System, version 2 (CFSv2), model (CFSsmcm) in lieu of the preexisting simplified Arakawa–Schubert (SAS) cumulus scheme. A detailed analysis of the tropical intraseasonal variability (TISV) and convectively coupled equatorial waves (CCEW) in comparison with the original (control) model and with observations is presented here. The last 10 years of a 15-yr-long climate simulation are analyzed. Significant improvements are seen in the simulation of the Madden–Julian oscillation (MJO) and most of the CCEWs as well as the Indian summer monsoon (ISM) intraseasonal oscillation (MISO). These improvements appear in the form of improved morphology and physical features of these waves. This can be regarded as a validation of the central idea behind the SMCM according to which organized tropical convection is based on three cloud types, namely, the congestus, deep, and stratiform cloud decks, that interact with each other and form a building block for multiscale convective systems. An adequate accounting of the dynamical interactions of this cloud hierarchy thus constitutes an important requirement for cumulus parameterizations to succeed in representing atmospheric tropical variability. SAS fails to fulfill this requirement, which is evident in the unrealistic physical structures of the major intraseasonal modes simulated by CFSv2 as documented here.


2014 ◽  
Vol 35 (10) ◽  
pp. 3102-3119 ◽  
Author(s):  
Hemantkumar S. Chaudhari ◽  
Samir Pokhrel ◽  
Subodh K. Saha ◽  
Ashish Dhakate ◽  
Anupam Hazra

2013 ◽  
Vol 118 (3) ◽  
pp. 1312-1328 ◽  
Author(s):  
Xingwen Jiang ◽  
Song Yang ◽  
Yueqing Li ◽  
Arun Kumar ◽  
Wanqiu Wang ◽  
...  

2013 ◽  
Vol 42 (7-8) ◽  
pp. 1925-1947 ◽  
Author(s):  
J. S. Chowdary ◽  
H. S. Chaudhari ◽  
C. Gnanaseelan ◽  
Anant Parekh ◽  
A. Suryachandra Rao ◽  
...  

2015 ◽  
Vol 143 (11) ◽  
pp. 4660-4677 ◽  
Author(s):  
Stephen G. Penny ◽  
David W. Behringer ◽  
James A. Carton ◽  
Eugenia Kalnay

Abstract Seasonal forecasting with a coupled model requires accurate initial conditions for the ocean. A hybrid data assimilation has been implemented within the National Centers for Environmental Prediction (NCEP) Global Ocean Data Assimilation System (GODAS) as a future replacement of the operational three-dimensional variational data assimilation (3DVar) method. This Hybrid-GODAS provides improved representation of model uncertainties by using a combination of dynamic and static background error covariances, and by using an ensemble forced by different realizations of atmospheric surface conditions. An observing system simulation experiment (OSSE) is presented spanning January 1991 to January 1999, with a bias imposed on the surface forcing conditions to emulate an imperfect model. The OSSE compares the 3DVar used by the NCEP Climate Forecast System (CFSv2) with the new hybrid, using simulated in situ ocean observations corresponding to those used for the NCEP Climate Forecast System Reanalysis (CFSR). The Hybrid-GODAS reduces errors for all prognostic model variables over the majority of the experiment duration, both globally and regionally. Compared to an ensemble Kalman filter (EnKF) used alone, the hybrid further reduces errors in the tropical Pacific. The hybrid eliminates growth in biases of temperature and salinity present in the EnKF and 3DVar, respectively. A preliminary reanalysis using real data shows that reductions in errors and biases are qualitatively similar to the results from the OSSE. The Hybrid-GODAS is currently being implemented as the ocean component in a prototype next-generation CFSv3, and will be used in studies by the Climate Prediction Center to evaluate impacts on ENSO prediction.


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